Böcker av Ludwig Fahrmeir

Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book's dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented.The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference.In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book.The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.

This book offers an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. It presents the most important models and methods on a solid formal basis and includes case studies.

The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.

In dieser Einführung werden erstmals klassische Regressionsansätze und moderne nicht- und semiparametrische Methoden in einer integrierten, einheitlichen und anwendungsorientierten Form beschrieben. Die Darstellung wendet sich an Studierende der Statistik in Wahl- und Hauptfach sowie an empirisch-statistisch und interdisziplinär arbeitende Wissenschaftler und Praktiker, zum Beispiel in Wirtschafts- und Sozialwissenschaften, Bioinformatik, Biostatistik, Ökonometrie, Epidemiologie. Die praktische Anwendung der vorgestellten Konzepte und Methoden wird anhand ausführlich vorgestellter Fallstudien demonstriert, um dem Leser die Analyse eigener Fragestellungen zu ermöglichen.

Dieses Arbeitsbuch ergänzt perfekt das Lehrbuch Fahrmeir/Künstler/Pigeot/Tutz: Statistik - Der Weg zur Datenanalyse. Es bietet eine Fülle von Aufgaben inklusive Lösungen und Computerübungen mit realen Daten. Es dient damit der Vertiefung und der Einübung des im Lehrbuch vermittelten Stoffes zur Wahrscheinlichkeitsrechnung, deskriptiven und induktiven Statistik. Die 5. Auflage enthält eine Reihe neuer Aufgaben, die hauptsächlich in Klausuren verwendet wurden.